In general, a bar code symbology identification process is performed for the purpose of classifying, transporting and delivering objects. The bar code symbology identification process involves obtaining information for automatically classifying the objects, gaining information to be recorded and managed through the use of a stop sensor and a height sensor, and automatically calculating a volume of the object based on the information attained by the stop sensor and the height sensor and a ROI search result.
Conventionally, only the information for classifying the objects has been utilized among information obtained by an image processing technique. Further, since a great amount of time is required to search for a bar code symbology by using a bar code symbology reading machine, it is very difficult to read more than one bar code symbology. In particular, in case the object has a large volume or area, it is impossible to read more than one bar code symbology.
Furthermore, a separate volume measurement system is required in the prior art in order to generate the volume information of the object while concurrently identifying the bar code symbology.
Generally, a bar code symbology reader system includes the steps of binarizing an image of the object in order to search for a bar code symbology at a high speed, extracting an edge of a black region and comparing the extracted edge with characteristic values of the bar code symbology. In case the bar code symbology declines over a predetermined angle, the bar code symbology reader system generates a central axis based on coordinates of the ROIs and examines all the ROIs to obtain a symbology pattern value. However, if a single threshold is applied in binarizing the object image, the possibility of finding a wrong bar code symbology region is very high since the threshold of the obtained image varies depending on a brightness distribution of an illumination and, thus, a bar code symbology may not satisfy even a requirement of the ROI in such case. In the mean time, even if multiple thresholds are utilized in order to overcome the above-mentioned problem, a great amount of time is required since each threshold should be applied for the whole image of the object or for searching for the ROIs of the object.
A bar code reader system using the above described technique, e.g., the bar code reader system disclosed in U.S. Pat. No. 6,193,158, performs the steps of setting a block size for the object image, generating vertical and horizontal grid lines at a predetermined distance and examining the above image in order to find bar code symbologies. However, the number of grid lines is so large that a great amount of time is consumed in order to calculate coordinate values of ROIs for the bar code symbologies existing on the vertical and the horizontal grid lines. The required time further increases since the vertical grid lines and their neighboring grid lines should be all examined in order to generate the coordinate values of the ROIs based on the examination result of the vertical grid lines. Further, if a bar code symbology declines by a certain angle, an error range of the image values obtained on the horizontal and the vertical grid lines should be estimated. In addition, if a part of character lines similar to the bar code symbology exists on the vertical or the horizontal grid lines, a number of ROIs may be wrongly selected. Moreover, if the bar code symbology has a short length or a small height, a larger number of grid lines should be generated, thus consuming a greater amount of time than in the case where the grid lines are set at a fixed interval.
In a conventional method for obtaining the bar code symbology information, the information is obtained and estimated by using a ladder structure. If the information of a to-be-read grid line overlaps with information of another grid line according to the inclination angle of the bar code symbology, however, the overlapped region should be removed.
In particular, if the grid lines are too short or too long and if a width of a bar is too narrow or too wide, a method for searching for geometry feature information of the bar, except for a curve shape, is employed in order to the ROIs of the bar code symbology. In examining the ROIs of the bar code symbology, the ROIs can be interpreted by calculating the two-dimensional information based on directional information and edges of the bar, selecting character images as ROIs in case of including a straight line component and interpreting all the image information in the ROIs.
Further, a method for checking whether a start and a stop bar region are coincident with a start and a stop pattern of to-be-read bar code symbology or with those of another bar code symbology is applied in order to identify the type and the direction property of a symbology. Thus, in case a bar code symbology, e.g., a bar code symbology contained in an international standard ISO/IEC/JTC1/SC31), not included in a system employing the above method is to be read, another identification method suitable for such a bar code symbology should be added to the image processing module. Further, since a method for verifying the state of the bar code symbology obtained as an image can be found in a decoding process and the start and the stop symbology can be also examined by the aforementioned information interpretation module, there occurs a problem that the same function is performed twice. Due to the complicated process as described so far, it is almost impossible to read more than two bar code symbologies. Further, it is also difficult to create the volume information of the object at the same time.
Furthermore, a method for setting in the decoding process three stages having a Low stage, setting a variable region in a middle stage of the three stages and calculating variations of a thickness of the bar code symbology and a value of a white region is conventionally applied in order to exactly obtain the thickness of the bar code symbology and the white region value. In this method, in order to prevent a wrong determination of the symbology value due to the brightness variation of the illumination generated by fixing a threshold value, a process for comparing ratio values of the symbology each other is included, so that it leads to a great amount of operation time. Further, though different gray level values can be applied according to their magnification, a high value with the threshold value fixed is obtained even in a narrow bar if well illuminated. Accordingly, there still exists a possibility of obtaining a wrong symbology value in case the bar code symbology is decided based on varied thickness of the bar code symbology and value of a white region or a reference value is applied as the magnification value of the narrow bar.